Moodscape: Adaptive Environment Based on User Mood

Abstract

In today’s fast-paced world, stress and anxiety have become common challenges, often affectingmentalwell-being.MoodscapeisaninnovativeAI-poweredapplicationdesigned toofferapersonalizedescapebycreatingimmersivevirtualenvironmentsbasedonauser’s emotions. By analyzing facial expressions using OpenCV and interpreting voice input through microphone-based sentiment analysis, the system detects the user’s mood in real time. Machine learning algorithms process these inputs to classify emotions, which then guide the generation of a corresponding virtual environment. Whether a user is feeling overwhelmed,sad,orjoyful,Moodscapecraftsadynamicexperiencethatalignswiththeir emotions,providingasenseofrelaxationandmentalrelief.Thisapproachmakesemotional well-being more accessible, especially for those unable to take breaks due to work or financialconstraints.ByintegratingAI,VR,andsentimentanalysis,Moodscapepresentsa cost-effective and engaging solution to stress management, promoting mindfulness and emotional balance.

Introduction

The text introduces Moodscape, an AI-driven application designed to improve mental well-being by creating virtual environments that adapt in real time to a user’s emotional state. Using facial expression recognition (via OpenCV) and voice tone analysis through machine learning, Moodscape detects moods such as stress or joy and generates corresponding immersive VR scenes (e.g., a calming beach for stress). This offers an accessible, personalized relaxation alternative to traditional methods like meditation or therapy, which may not always be practical.

The literature review covers related topics such as video conferencing technologies, WebRTC applications, quality of experience in telemeetings, and the usability of mobile video conferencing apps, emphasizing the importance of emotional communication and user experience.

The core problem addressed is the lack of intuitive, real-time technology for emotional relief amid modern life stress. Moodscape’s methodology combines AI, machine learning, and VR to analyze user input and deliver tailored virtual relaxation environments instantly.

Evaluation results showed Moodscape’s mood detection is accurate and the virtual environments effectively enhance relaxation, with positive user feedback. Areas for improvement include better emotion sensitivity and increased realism of virtual settings. Overall, Moodscape offers an innovative, practical solution for managing stress and promoting mental wellness through AI-powered emotional intelligence and immersive technology.

Conclusion

Moodscape presents an innovative approach to mental wellness by leveraging artificial intelligenceandvirtualrealitytocreatepersonalizedrelaxationexperiencesbasedonreal- time emotion detection. By analyzing facial expressions and speech tone, the system accurately determines a user’s mood and generates immersive environments that align withtheiremotionalstate,providinganaccessibleandeffectivewaytomanagestressand enhancewell-being.Userfeedbackandsystemevaluationsdemonstratedtheapp’sability tooffermeaningfulemotionalrelief,withparticipantsexperiencinganoticeablereductionin stress levels through AI-driven virtual experiences. While further refinements in emotionclassificationandenvironmentrealismcanenhanceitseffectiveness,Moodscape has already proven its potential as a powerful tool for mental relaxation. By combining AI, machine learning, and VR, it offers a cost-effective and engaging solution for individuals seeking an escape from daily stress, making emotional well-being more interactive, intuitive, and accessible.

References

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Copyright

Copyright © 2025 Bhagyashree Hugar, Indra M, Kalavakuri Soumya Sree, M Deepa, Srinath Devale. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.